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Life cycle analysis of macauba palm cultivation:
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a promising crop for biofuel production
2
3
Ignacio A. Fernández-Coppel1, Anderson Barbosa-Evaristo2, Adriana Corrêa-Guimarães3, 4
Jesús Martín-Gil3, Luis M. Navas-Gracia3 and Pablo Martín-Ramos4*
5 6
1 Engineering of Manufacturing Processes group, School of Industrial Engineering, University 7
of Valladolid, C/ Francisco Mendizábal 1, 47014 Valladolid, Spain.
8
2 Instituto de Ciências Agrárias (ICA), Universidade Federal dos Vales Jequitinhonha e Mucuri 9
(UFVJM), 38610-000 Unaí, Brazil.
10
3Department of Agricultural and Forestry Engineering, ETSIIAA, University of Valladolid, 11
Avenida de Madrid 44, 34004 Palencia, Spain.
12
4 EPS, Instituto de Investigación en Ciencias Ambientales (IUCA), University of Zaragoza, 13
Carretera de Cuarte s/n, 22071 Huesca, Spain. E-mail: [email protected]; Tel: +34 (974) 292668;
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Fax: +34 (974) 239302.
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Abstract 17
The 450 Scenario, which limits the increase in global average temperature to 2 ºC, makes it 18
necessary to take steps towards a low-carbon economy. Since the energy sector is a major 19
contribution to anthropogenic greenhouse gas (GHG) emissions, the production of biofuels can 20
play a key role in strategies aimed at climate change mitigation. In this regard, the oil derived 21
from macauba palm (Acrocomia aculeata), mainly constituted of saturated organic chains, has 22
been claimed to hold promise for the production of liquid fuels. The high potential yield, 23
diversity of co-products and various positive features of this emerging energy crop make it an 24
interesting option both from a social and an environmental point of view. Nonetheless, a full 25
environmental evaluation is still missing. In the study presented herein, the impacts produced in 26
its plantation, cultivation and harvesting phases and the associated cumulative energy demand 27
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have been determined using a life cycle analysis methodology, in addition to shedding some 28
light on its GHG intensity relative to the other energy crops it can displace. Excluding land use 29
changes and biogenic CO2 fixed by the crop, it was concluded that to produce one ton of 30
macauba fruit in Brazil, the system would absorb 1810.21 MJ, with GHG emissions of 158.69 31
kg CO2eq in the 20-year timeframe, and of 140.04 kg CO2eq in the 100-year timeframe 32
(comparable to those of African oil palm). Damage to human health, ecosystem quality, and 33
resources would add up to 16 Pt·t-1 according to Eco-indicator 99 methodology. In order to 34
account for the uncertainty derived from improvement and domestication programs, which 35
should affect current production levels, a sensitivity analysis for different productivities was 36
performed. In all analyses, fertilization was found to be responsible for ca. 90% of the impacts, 37
and hence special attention should be paid to the development of alternative fertilizer 38
management schemes.
39 40
Keywords: Acrocomia aculeata; bioenergy; Brazil; life cycle assessment (LCA); macauba;
41
sustainability.
42 43
1. INTRODUCTION 44
The increase in the energy needs for the development of our world opens the door to new 45
sources of energy that can be used as biofuels. In this regard, the Intergovernmental Panel on 46
Climate Change (IPPC) has stressed that bioenergy can play a key role in the mitigation of 47
climate change, but has also highlighted the need to take into consideration the sustainability of 48
practices and the efficiency of technologies. Thus, there is a need for crops with low emissions 49
throughout their life cycle, compatible with land sustainable management, with a low water 50
footprint, etc.
51
Amongst the emerging agroforestry crops with a high energy potential, macauba palm 52
(Acrocomia aculeata (Jacq.) Lodd. ex Mart.) has been claimed to hold particular promise 53
(Berton et al., 2013; Coimbra and Jorge, 2012; Montoya et al., 2016). It can be dedicated to the 54
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direct mitigation of climate change, due to its ability to contribute to the production of biomass 55
of high energetic power, through esterification, and therefore of bioenergy.
56
Macauba palm presents an interesting productivity that places it among the main agro-energy 57
crops: 25 t fruit·ha-1·yr-1 with a high oil content (50-75%), that is, 6200 kg of oil·ha-1·yr-1, 58
comparable to the productions obtained from African oil palm (Elaeis guineensis Jacq.) 59
(Cargnin et al., 2008; César et al., 2015; Ciconini et al., 2013; Pires et al., 2013). Given the good 60
prospects for its genetic improvement and domestication, current production is expected to rise 61
above 6500 kg oil·ha-1·yr-1, provided that in recent studies the figures for extracted oil have 62
already exceeded this amount for scenarios of 400 plants·ha-1, surpassing even African oil palm 63
in terms of liters of biodiesel·ha-1 (Colombo et al., 2017; Luis and Scherwinski-Pereira, 2017;
64
Vianna et al., 2017).
65
This palm has similar characteristics to those of other forestry or agricultural residues widely 66
used in the production of biofuels, and is already acclimated to subtropical climates because it is 67
native to Brazil (Cardoso et al., 2017; César et al., 2015). Such adaptation of macauba to a high- 68
range of hydrothermal stressors facilitates the extension of its cultivation and exploitation to 69
marginal lands with grassland coverings and its implantation in slopes. Further, it is suitable for 70
the regeneration of burned land without plant cover (Motoike and Kuki, 2009).
71
Macauba palm can open up a wide range of possibilities upon combination with livestock 72
activity, with associated savings in fertilizers and the elimination of herbicides throughout the 73
life cycle of the crop (Araújo et al., 2017; Delucchi, 2010). By-products generated after the 74
extraction of the oil are susceptible of use as animal feed (Ali et al., 2017a; Ali et al., 2017b;
75
Costa Júnior et al., 2015; Henrique Bernardes Pereira et al., 2013), and the endocarp of the fruits 76
can be employed for vegetal carbon production (Bhering, 2009; Ministério do Desenvolvimento 77
Agrário, 2014), as a biosorbent for heavy metals removal in wastewater (Altino et al., 2017;
78
Vieira et al., 2012), or for biokerosene production (Cardoso et al., 2017; Zelt, 2018). Finally, 79
other alternative uses would be related to the potential applications of the bioactive compounds 80
present in its oil and in some other plant by-products (Dario et al., 2018; Lescano et al., 2014;
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Oliveira et al., 2016; Shahidi and de Camargo, 2016; Souza et al., 2017a).
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Amongst the positive characteristics of this crop, one may also count its potential for poverty 83
reduction and local economic development, acting as a source of employment, contributing to 84
rural development and to population fixation (Lopes et al., 2013).
85
However, regardless of aforementioned advantages, no system should be considered a priori 86
as acceptable or optimal without having studied all the involved aspects that generate emissions 87
of GHGs. The goal of this study has been to evaluate if this agroforestry crop can help mitigate 88
some of the great challenges that climate change entails for the future of the planet, and if its 89
introduction can be deemed as a strategy of adaptation to climate change and a maneuver aimed 90
at the de-carbonization of the environment in a short-term time horizon. To do so, the study 91
presented herein aims to assess the emissions produced by macauba palm plantation, cultivation 92
and harvesting in Minas Gerais, Brazil. By using a life cycle analysis (LCA) methodology, the 93
direct and indirect impacts that affect the ecosphere (Singh et al., 2013) have been estimated, a 94
sensitivity analysis has been performed, and a semi-quantitative comparison with other energy 95
crops has been conducted, paying particular attention to African oil palm. Possible adaptation 96
and mitigation strategies are outlined.
97 98
2. MATERIALS AND METHODS 99
2.1. Life cycle analysis methodology 100
A LCA methodology was chosen to study the potential impact on the environment per ton of 101
macauba fruit produced (and transported to an oil extraction factory 40 km far from the 102
plantation). Inflows (resources) and environmental outflows (emissions), were studied 103
according to ISO 14040: 2006 (Environmental management - Life cycle assessment - Principles 104
and framework), selecting an attributional LCA (ALCA) methodology (Plevin et al., 2014;
105
Recchia, 2011) to faithfully represent the environmental burden needed to produce our 106
functional unit. This approach focuses on the physical flows with environmental relevance to 107
and from a life cycle and its subsystems, tracking the energy and material used throughout the 108
supply chain of the crop studied, including all flows of the agroforestry crop (understanding the 109
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crop as a product system) throughout the agricultural operations necessary to produce it, to 110
harvest it and to transport it to the industry of extraction and process.
111
The ALCA model was preferred over the consequential LCA (CLCA) because the latter is 112
oriented to the description of how these flows are affected by the economic or policy context, 113
and thus would be more oriented to decision making.
114 115
2.2. Goal and scope 116
The objective of this study was to assess the macauba palm product system by systematically 117
evaluating the environmental impacts per ton of macauba fruit –assuming a production of 900 118
t·ha-1 in 30 years–, including the generation of pre-seedlings, seedlings, field preparation, 119
planting, cultivation, harvesting and transport of fruits to the gate of industry were they will be 120
transformed into biodiesel. The industrial phase was excluded from the analysis because of the 121
lack of a well-established and representative biodiesel production procedure for this cropa. 122
Consequently, the study included the input/output flows of raw materials, as well as energy 123
and human and animal labor. All required services (inputs, such as the transport involved to 124
provide fertilizers to the crop) and all emissions to the environment were evaluated at the 125
inventory stage (European Commission et al., 2010).
126
The ALCA “cradle to farm gate” analysis can be regarded as an “upstream” approach from 127
the oil extraction industry that gives added value to the macauba. Chronologically, it 128
encompasses all inventory phases that occur before “gate to gate” impacts can occur, prior to the 129
a It is worth noting that at present there is no consensus on any of the manufacturing stages. For instance, different approaches have been proposed for the oil extraction: using compressed propane (Trentini et al., 2017b); using n-hexane, ethyl acetate and isopropanol at low pressure (Trentini et al., 2016); by Soxhlet method with ethanol, hexane and ethyl ether (Lescano et al., 2015); using ethanol and isopropanol (Trentini et al., 2017a); etc. Moreover, different storage conditions and treatments would also need to be assessed, as they influence oil quality (Evaristo et al., 2016b). Further, there is not an agreement either on which would be the best method for conversion to biodiesel (viz., supercritical method, enzyme hydroesterification, alkaline transesterification by homogeneous catalysis with microwave irradiation, cold-flow esterification and transesterification using different alcohols, etc.) (Pereira et al., 2016; Silva et al., 2016; Souza et al., 2016).
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entry of the harvested raw material –with high calorific value– to the processing industry 130
(biodiesel production).
131 132
2.3. Indicators 133
Depending on the goal and scope of the study, one or more impact categories may be 134
included in the life-cycle impact assessment (LCIA). While global warming potential (GWP) 135
and energy consumption are often included in bioenergy system LCAs, a full environmental 136
evaluation should consider other categories related to impacts to soil, water, air, human health, 137
and ecosystems (Cherubini and Strømman, 2011; Muench and Guenther, 2013). Thus, to 138
determine the environmental burden generated by the product system, relevant impacts were 139
evaluated through three different indicators, estimating in a quantitative manner: (i) the primary 140
energy demand (with Cumulative energy demand (CED) v.1.09 method); (iii) the GHGs 141
emissions (with IPPC 2013 methodology); and (ii) the damage in terms of emissions, land use 142
and resource depletion (with Eco-indicator 99 methodology).
143
2.3.1. Cumulative energy demand 144
As regards the quantitative estimation of the total energy demand in the life cycle of the 145
system, CED v.1.09 provides a measure of the primary energy demand of the product, that is, 146
the energy content of energy carriers that have not yet been subjected to any conversions, while 147
taking losses due to transformation and transport fully into account. The necessary energy per 148
functional unit is expressed in MJ, and normalization is not part of this method.
149
Characterization factors are divided in 5 impact categories: non-renewable, fossil; non- 150
renewable, nuclear; renewable, biomass; renewable, wind, solar, geothermal; and renewable, 151
water (Frischknecht et al., 2007; Weidema et al., 2013).
152
2.3.2. IPCC 2013 methodology 153
The IPCC 2013 method is the successor of the IPCC 2007 method and has been developed 154
on the basis of the Climate Change 2013 report (IPCC, 2014). This method evaluates the factors 155
that affect climate change with a timeframe of 20 and 100 years, using CO2eq units. However, 156
the characterization factors do not include the indirect NO2 formation of nitrogen emissions; do 157
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not take into account the radiative forcing from NOx, water, sulfate, etc. emissions in the lower 158
stratosphere or in the upper troposphere; do not take into consideration the range of indirect 159
effects proposed by the IPCC; and do not include the formation of CO2 by CO emissions. The 160
methodology used in this study corresponded to version 1.02 (March 2016) for the 20-year 161
timeframe and to version 1.09 (August 2014) for the 100-year timeframe.
162
2.3.3. Eco-indicator 99 methodology 163
Eco-indicator 99 (EI-99) is a damage-oriented methodology for calculating the impacts on 164
three main categories (endpoints): damage to human health, expressed in DALY ("disability 165
adjusted life years") units; damage to ecosystem quality, measured in PDF·m2·yr, where PDF 166
stands for "potentially disappeared fraction"; and damage to resources, measured in MJ of 167
surplus energy. As regards the weighting model, in this study the egalitarian archetype was 168
chosen, which has a very long term perspective and that takes into account all possible effects.
169
The aggregated LCA results are expressed in points (Pt) per unit of analyzed material/process.
170 171
2.4. Functional unit and system boundaries 172
In the study presented herein, the functional unit was a metric ton of macauba with 36%
173
humidity.
174
The system boundaries are depicted in Figure 1. They included the production of pre- 175
seedlings (nursery), seedlings, preparation of the land, planting, cultivation, harvesting and 176
transport to the extractive industry located 40 km apart from the plantation. The transportation 177
of the necessary machinery to carry out the planting, the transportation of the fertilizers and 178
agrochemical products, and -in general- all the inflows and outflows of each of the two systems 179
(technological and natural) that integrate the ecosphere were also taken into consideration.
180
[FIGURE 1]
181
The use of the macauba crop was assumed to be the extraction of oil for biofuel production, 182
either in its purest state or as a base for mixing with other hydrocarbons. The production or use 183
of by-products was not taken into consideration in the system (see section 2.10, in which all 184
items excluded from the analysis are detailed), which was limited only to the primary 185
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production of the functional unit. Further, any interaction of aforementioned functional unit 186
with other products or systems that are not part of this study, such as economic interactions or 187
interactions with other non-evaluated technical systems, was discarded (since they cannot be 188
taken into account in an ALCA methodology). Intending to include all these interrelations 189
would surely alter the output of the results object of the study.
190 191
2.5. Assumptions 192
It should be clarified that, in relation to the spatiotemporal location of the study, it was 193
conducted with data referring to Minas Gerais, Brazil in 2017, which that cannot be directly 194
extrapolated to other regions (Chiaramonti and Recchia, 2010; Ossés de Eicker et al., 2010). For 195
the extrapolation of crop LCA, the use of Modular EXtrapolation of Agricultural LCA 196
(MEXALCA) method would be the preferred approach, as it does not discard processes nor 197
jeopardize the understanding of the production system upon derivation of LCIA results for a 198
crop in a specific (target) country using the LCIA data of the same crop in another (original) 199
country (Roches et al., 2010).
200
A plantation of macauba palm with an extension of 30 hectares, 40 km far from a medium- 201
sized city of about 15,000 inhabitants (Mirabella, State of Minas Gerais, Brazil) and 70 km far 202
from a large city of 360,000 inhabitants (Montes Claros, State of Minas Gerais, Brazil) is 203
proposed.
204
The selected area for the plantation is in the Minas Gerais (Brazil) region, near 16°29'54.90"
205
S, 44°4'12.43" W geographical coordinates, at an altitude of 818 m above sea level. This region 206
is part of a neotropical savannah that includes parts of Brazilian federal states and extends from 207
the Equator to the Tropic of Capricorn, and is representative of the potential growing areas for 208
this agroforestry crop (Falasca et al., 2016). According to Köppen classification, the Cerrado 209
biome exhibits a typical Aw climate (humid tropical savannah) with a distinct dry season 210
between May and September. The average annual precipitation is 1200 mm.
211
Since in this area there are no commercial plantations older than seven years, both 212
consumption and production have had to be estimated beyond the 8th year.
213
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The total amounts of inputs/machinery/human labor per hectare of macauba palm plantation 214
is summarized in Table S1. The transport of raw materials/machinery was assumed to be carried 215
out from different centers/cities: for the production of macauba pre-seedlings, 366 km; for the 216
production of macauba seedlings and their transportation to the plantation, 366 km; for the 217
heavy machinery rented for the land preparation and planting operations: 70 km; for the 218
purchase of machinery (tractors and agricultural machinery) for agroforestry tasks, 40 km; for 219
the acquisition of fertilizers (6:30:6, 20:5:20, 10:10:10 nitrate, phosphorus, potassium, with 220
boron, zinc, copper, urea, lime and KCl microelements), 70 km; and for the acquisition of 221
agrochemicals (herbicides and insecticides, in particular thermicides and formicides), 70 km.
222
Transportation media have been restricted to those currently existing in Brazil, employing a 223
maximum payload of 20 t.
224
The fertilization treatments discussed in previous paragraph was deemed as optimal to 225
maximize fruit production in the agrometeorological conditions of the area of study. The 226
objective was to provide plants with the necessary macro- and microelements to complete their 227
vegetative cycle, obtaining a favorable development and an excellent productivity, without 228
introducing factors that could alter the potential of biomass per unit of area (Machado et al., 229
2015).
230
The extraction, esterification or final disposal of the residues generated by the crop in its 231
industrial phase were not included, and no recovery, reuse, recycling or use of by-products that 232
can be obtained from the waste generated from the macauba plantation were considered (see 233
section 2.10). For instance, the agricultural by-product obtained from the exploitation of the 234
palm trees referred to as "tusa" (empty palm bunch, rachis of the macauba), which is a 235
lignocellulosic material that contains 60-65% moisture and 1-3% vegetable oil, was not taken 236
into consideration. The phase of use of the biofuel generated after the industrial extraction phase 237
was not considered either.
238
The expected macauba production was estimated by sampling 100 wild (non-cultivated) 239
macauba plants in the surroundings of the plantation considered in this paper. The number of 240
fruit bunches was counted, resulting in an average of 2.39 bunches per plant, with a standard 241
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deviation of 1.37 and a median of 2. For these same 100 wild macauba plants, fruits were 242
weighed, obtaining an average of 24.52 kg of fruit per bunch with a standard deviation of 8.27 243
and a median of 24.58 kg per bunch. Thus, considering 461 macauba palm trees arranged in a 244
5×5 m frame equilateral triangle distribution (i.e., 21.65 m2 per macauba palm tree), with an 245
average of 2.39 bunches per palm tree and an average weight of 24.52 kg of fruit per bunch, a 246
total production per hectare of 900 t over the 30 years of cultivation would result. This would be 247
in good agreement with the results reported by Lopes and Steidle Neto (2011).
248
A propos of the use of the land, it was supposed that it was not modified (see section 2.10), 249
conserving the silvopastoral exploitation system (i.e., the destruction of forest or the change of 250
land use were not contemplated in the study). To include the effect of indirect land use change 251
effects (ILUC) on GHGs, a CLCA would be needed (McManus and Taylor, 2015; Plevin et al., 252
2014; Rajagopal, 2014), which is beyond the scope of this work.
253 254
2.6. Data and data quality 255
The data used in the LCA corresponded to current and real agricultural production processes 256
that use cultivation methods, raw materials, phytosanitary products, fertilizers (NPK) and 257
machinery for African oil palm production.
258
Both the machinery used and the means of transport corresponded to the geographical area 259
where the study was carried out (Minas Gerais, Brazil) and to agricultural processes, machinery 260
and conditions that are currently in force. Existing technologies were used for the materials, 261
products and agroforestry area that came into play, appropriate for a limited geographic area as 262
well as for a defined spatiotemporal window (less than three years from the obtaining of the data 263
to the preparation of this study).
264
These data satisfied all the requirements to define the chosen functional unit and ensured that 265
the study was within the defined system limits.
266
The integrity used in this study was higher than 97% (percentage of measured or estimated 267
flow). The remaining 3% would not be representative and would have no significant impact on 268
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the study as a whole. No phase or stage that was expected to modify either the conclusions or 269
objectives of the study was excluded.
270 271
2.7. Life cycle inventory 272
The life cycle inventory (LCI) was carried out with the following databases (with data 273
updated as of June 2017 and that corresponded to the year 2017): Ecoinvent 3.4, Agri-footprint, 274
EL CD, Industry data 2.0, LCA food DK, EU & DK Input Output Database, Methods (based on 275
existing ESU database in Swiss IO Database), Swiss Input Output Database, USA Input Output 276
Database, US Database System Expansion and USLCI.
277 278
2.8. Allocation 279
The allocation of the inflows/outflows of the different products was carried out by means of 280
a “physical allocation” with data on the energy used and from the mass/quantity and hourly 281
distribution of each one of the tasks of each of the processes considered throughout the entire 282
cultivation process. All the stages and sub-stages leading to the functional unit result were taken 283
into account.
284 285
2.9. Reproducibility, coherence and representativeness 286
The LCA of the functional unit under study can be deemed as reproducible by culture 287
methods that can be produced with the same inputs and outputs into the environment taken into 288
account in this study. All the necessary data are available and complete in this work, so that it 289
can be repeated in an experimental manner. The data used in this LCA study are technically and 290
scientifically valid and are in accordance with the reality of the country where it is 291
geographically located. The data handled in this study (viz. processes, flows, materials, tillage, 292
labor and energy required) are representative of current cultivation processes, geographically 293
referred to Minas Gerais, Brazil and with a space-time window of three years, to ensure an 294
optimal representativeness of each of the handled parameters.
295 296
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2.10. Further clarifications to the study 297
Explicit consideration shall be given to the possible limitations of the conclusions due to 298
parts of the product system that were excluded from the analysis. The following points were 299
intentionally not taken into consideration in this study:
300
− The effects of soil transformation from pasture/woodland into agroforestry land. As 301
noted above, the current use of the land is conserved, not generating deforestation of 302
virgin jungle or lands with a current silvicultural use.
303
− The impact on biodiversity due to land use transformation.
304
− The externalities created by the cultivation of the macauba, such as by-products 305
susceptible to employment in animal feed, charcoal generation, etc.
306
− The use of by-products from pruning/harvesting in animal feed or other use.
307
− The CO2 emitted by the burning of by-products of the macauba plantation.
308
− The biogenic CO2 fixed by the crop in the plant mass created by the plantation.
309
− NH3, N2O, N2 and NO emitted by the plantation to the atmosphere.
310
− The burning of residues during land preparation, their destruction or the originated CO2. 311
− The coverage of the land with other crops associated with the macauba during the initial 312
stages of growth, until it enters into production.
313
− The emissions produced by the pruning waste deposited in the soil, biomass in 314
decomposition.
315
− The percolation of fertilizers, N and K, from the soil of the plantation.
316
− The contamination with heavy metals (Hg, As, Cr, Se, Ni, Mo, etc.) by percolation 317
resulting from the use of fertilizers.
318
− The emissions produced when using pesticides in the plantation.
319
− The emissions derived from land cover in the plantation, decomposing biomass.
320
− The recycling of polyethylene from the bags of macauba seedlings.
321
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− The recycling / reuse of fertilizer containers (sacks), insecticides / phytosanitary / 322
formicidal / insecticide containers at a packaging of plant protection products waste 323
collection point.
324
− The recycling of seedling containers and polystyrene trays.
325
− The empty return and the average load of the means of transport in the material 326
transport system.
327
− The necessary infrastructures for the implementation, handling and transport of the 328
products.
329
− The elimination of the plantation once it reaches the end of its production period (after 330
30 years).
331 332
2.11. Software 333
Simapro v.8.2.0.0 software (PRé Sustainability, Amersfoort, The Netherlands) was used in 334
this study.
335 336
3. RESULTS 337
3.1. Cumulative energy demand methodology 338
As regards the quantitative estimation of the total energy demand in the life cycle of the 339
system, the obtained result for the case of study was 1810.21 MJ per ton of macauba fruit, 340
broken down into three main activities according to the following Sankey diagram (Figure 2a).
341
[FIGURE 2]
342
The energy embedded in the system would thus mostly correspond to the cultivation stage 343
(90.93%), followed by the harvest (6.98%) and the tree planting (2.09%). Attention should be 344
paid to the fact that 89.41% of the energy required in the cultivation stage would be invested in 345
activities related to the fertilization of the plantation.
346 347
3.2. IPCC 2013 methodology 348
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In relation to the climate change factors of IPCC with a timeframe of 20 years, the results are 349
shown in Figure 2b. The set of activities aimed at the maintenance and conservation of the 350
plantation would represent 92.87% of the total CO2 emissions per ton of fruit obtained. It is 351
worth noting that out of those 147.38 kg CO2eq·t-1 of fruit associated to the cultivation stage, 352
fertilizers would be responsible for 90.85% of the GWP.
353
The results for the 100-year timeframe are summarized in Table 1. In this case, the total 354
GWP would add up to 140.04 kg CO2eq per ton of macauba fruit. The cultivation stage would 355
involve 92.4% of the total emissions and, out of those 129.37 kg CO2eq·t-1, fertilizers would 356
account for 89.5% of the GWP.
357
[TABLE 1]
358 359
3.3. Eco-indicator 99 methodology 360
As concerns the impacts on air, water, soil, land use, land occupation, soil conversion, MJ 361
for material extraction, MJ of energy extracted, MJ of energy used, etc. created by the system, 362
they are summarized for the three main categories in Figure 3. It follows that the activity that 363
has the greatest damage to human health, to the quality of the ecosystem and to resources is the 364
cultivation stage, accounting for 92.1%, 88.4% and 89.4% of the total endpoints, respectively.
365
On the other hand, the initial plantation (which encompasses the pre-cuttings, cuttings 366
(saplings), open streets, land preparation and planting saplings operations) represented less than 367
2% of the damage in all the three categories.
368
[FIGURE 3]
369
A breakdown of the damage for all the impact categories is depicted in Figure 4. One may 370
observe that most of the impact associated to macauba cultivation corresponded to the 371
respiratory inorganics category (ca. 40%), i.e., respiratory health risks resulting from winter 372
smog caused by emissions of dust, sulphur and nitrogen oxides to air. Fossil fuels depletion 373
accounted for ca. 29% of the damage, followed by carcinogens (toxicological risk and potential 374
impacts of carcinogenic chemicals released into the air, water, soil, and agricultural soil), which 375
represented ca. 15% of the total damage, and by climate change (with ca. 9% of the total 376
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damage). The fossil fuel score can be ascribed to the amounts of fossil fuels used in the 377
agrochemicals production, in crop-related operations involving machinery (tilling) and in 378
transportation (both inside the plantation and from the plantation to the oil extraction factory), 379
which would also be responsible for the scores in respiratory inorganics and climate change.
380
The use of phytosanitary products and fertilizers would in turn be the main cause for 381
carcinogens.
382
[FIGURE 4]
383
If one focuses only on the cultivation stage, which –as noted above– would be responsible 384
for most of the damage, the impact throughout the 30 years of cultivation for several of the 385
operations is shown in Figure 5. The fertilizers used (viz. urea, phosphate fertilizer y potassium 386
fertilizer) would be responsible for 88% to 93.5% of the total impacts generated, depending on 387
the category, while the impact associated with lime, pyrethroid, glyphosate, 2,4- 388
dichlorophenoxyacetic acid, weed-killers, insecticides, formicides, mowing, transportation, etc.
389
would account for the ca. 10% remaining damage. This is line with other studies for other 390
energy crops (Ndong et al., 2009; Rodrigues et al., 2014; Siregar et al., 2015).
391
[FIGURE 5]
392 393
3.4. Sensitivity analysis 394
A sensitivity analysis was conducted by changing the productivity of the macauba crop per 395
hectare, provided that the ongoing domestication and breeding programs of this species for oil 396
yield –which have revealed specimens with a potential to produce as much as 10 t oil·ha-1·y-1 397
(Galembeck and Abreu Filho, 2017)– would represent an importance source of uncertainty that 398
could affect results and conclusions (Castro et al., 2017; Simiqueli et al., 2018). The inputs for 399
pre-cuttings, cuttings, the plantation and the cultivation were kept fixed, while those associated 400
with the harvest stage were modified (as a consequence of the differences in the transport of the 401
fruits inside the plantation and from the plantation to the oil extraction factory). Results are 402
summarized in Figure 6.
403
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As regards the CED, it would change from 1721.22 MJ·t-1 for a productivity of 800 t·ha-1 to 404
1449.33 MJ·t-1 for a productivity of 1000 t·ha-1 (ca. 34 MJ/25 t of fruit on average). Thus, 405
increasing the crop productivity from 800 to 825 t·ha-1 would decrease the CED by 2.90%, 406
while by increasing the productivity from 975 to 1000 t·ha-1 a 2.35% reduction would be 407
attained.
408
The GWP values with the IPCC 2013 methodology in the 20-year timeframe would range 409
from 177.48 kg CO2eq·t-1 to 143.66 kg CO2eq·t-1 for productivities of 800 t·ha-1 and 1000 t·ha-1, 410
respectively. This would imply that an increase in productivity of 25 t·ha-1 would entail, on 411
average, a reduction of ca. 4.2 kg CO2eq. As the productivity is increased, the changes are again 412
less marked: increasing the productivity from 800 to 825 t·ha-1 would decrease emissions by 413
2.96%, while increasing the productivity from 975 to 1000 t·ha-1 would decrease emissions by 414
2.4%.
415
If the 100-year timeframe is considered instead, the emissions would range from 156.55 kg 416
CO2eq to 126.82 kg CO2eq for productivities of 800 t·ha-1 and 1000 t·ha-1, respectively. In this 417
case, an average decrease of ca. 3.7 kg CO2eq would be attained upon an increase in 418
productivity of 25 t·ha-1. 419
Apropos of the damage to the environment, estimated with EI-99, it would vary between 420
17.83 Pt·t-1 (for a productivity of 800 t·ha-1) and 14.49 Pt·t-1 (for a productivity of 1000 t·ha-1).
421
An increase in crop productivity of 25 t·ha-1 would result in an average decrease of around 0.42 422
Pt, with a maximum decrease of 2.84% for the 800 to 825 t·ha-1 productivity improvement and a 423
minimum decrease of 1.92% for the 975 to 1000 t·ha-1 improvement.
424
[FIGURE 6]
425 426
4. DISCUSSION 427
4.1. Comparison with other energy crops 428
It should be stressed that the scarcity of case studies on LCA of the cultivation stage of 429
energy crops (most studies focus on the actual biofuel production stage (Castanheira and Freire, 430
2016)), together with the differences between studies (in terms of the chosen indicators, the 431
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assumptions, the boundaries, the secondary data, data quality, etc.), make it impossible to make 432
direct comparisons (Chiaramonti and Recchia, 2010; Shonnard et al., 2015). Furthermore, 433
although the majority of the studies in the literature have focused on GHG emissions and energy 434
requirements (Shonnard et al., 2015), there is no common agreement in relation to the units (i.e., 435
results may be expressed per ton of fruit/fresh fruit bunches, per ton of crude oil, per ton of 436
refined oil, per ton of biodiesel, per ha, per MJ, etc.), which further which jeopardizes the 437
comparison between studiesb. 438
For instance, the treatment of biogenic carbon may lead to significant differences in LCA 439
results: Rodrigues et al. (2014) studied the GHG balance of crude palm oil from E. guineensis 440
for biodiesel production in Brazil and concluded that the system worked as a carbon sink 441
because it fixed approximately 1.1 times more CO2 than it released: the system could attain a 442
sequestration of 166.42 kg CO2eq·t-1 of crude palm oil or up to 207.96 kg CO2eq·t-1 by partial 443
substitution of synthetic fertilizers by organic ones (a strategy from which the system presented 444
herein could also benefit). However, this negative emissions balance would result from taking 445
into consideration the large quantity of CO2 captured during the growth of palm trees, whereas 446
in the study presented herein such biogenic CO2 fixed by the crop in the plant mass created by 447
the plantation was excluded from the analysis, as noted in subsection 2.10. A reduction of 448
approximately 10 Mg·ha-1 of CO2 for each hectare planted with A. aculeata may be expected 449
throughout its production cycle (César et al., 2015).
450
Rivera-Méndez et al. (2017) analyzed the carbon footprint of the production of African oil 451
palm fresh fruit bunches (FFB) in Colombia and estimated the emissions in 118 kg CO2eq·t-1 of 452
fresh fruit bunches, slightly lower (ca. 8.8% lower) than the 129.37 kg CO2eq·t-1 estimated 453
herein for the cultivation stage of macauba.
454
Silalertruksa et al. (2017) studied the environmental sustainability of African oil palm cultivation 455
in different regions of Thailand. GHG emissions results (estimated using IPCC 2007 GWP100) 456
b For instance, refined oil and not crude oil should be used for the functional unit, since different crude oils contain different levels of impurities and free fatty acids that are removed in the refinery stage (hence, the crude oils are not substitutable in a one to one ratio) (Schmidt, 2015).
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varied over a large range: from 183 kg CO2eq·t-1 FFB in the Northeast and 137 kg CO2eq·t-1 FFB in 457
the North to 94 kg CO2eq·t-1 FFB in the South, depending on the productivity, growers’ practices 458
and the transport of raw materials. Stichnothe and Schuchardt (2011), who studied the GWP of 459
African oil palm production in Indonesia and Malaysia, also found GWP100 values (using 460
IPCC 2007 methodology) slightly above 100 kg CO2eq·t-1 FFB for its cultivation (excluding land 461
use change (LUC), since if rainforest or grassland is converted to palm oil plantations in 462
Malaysia or Indonesia, this would cause between 1850 and 425 kg CO2eq·t-1 of FFB). For 463
comparison purposes, the GWP100 (recalculated with IPCC 2007 methodology to allow 464
comparison) for macauba cultivation was 141.54 kg CO2eq·t-1 of fruit, so it would be close to or 465
slightly higher than the average GWP100 for African oil palm.
466
If one expresses the results per MJ, in a meta-analysis of over 70 environmental LCA studies of 467
liquid transportation biofuels in the Pan American region, Shonnard et al. (2015) concluded that the 468
GHG emissions (excluding the LUC effect) of African oil palm cultivation were on average 25 g 469
CO2eq·MJ-1. Taking a lower heating value for biodiesel of 37.1 MJ·kg-1 (Iriarte et al., 2012), a 470
density of 0.916 g·cm-3, and considering that 1 t of macauba fruit yields 200 l of biodiesel (Colombo 471
et al., 2017; del Río et al., 2016; Evaristo et al., 2016a), a GWP value of 23.34 g CO2eq·MJ-1 472
would result, which again is very similar to that of palm oil biodiesel.
473
In terms of CED, Harsono et al. (2012) studied the energy balances of E. guineensis oil 474
biodiesel in Indonesia and concluded that the total energy input for commercial plantations was 475
81.82 GJ·ha-1·yr-1. Subtracting the industrial phase and the land use change contributions, the 476
energy input would be 45.73 GJ·ha-1·yr-1. If one compares it with the values for macauba, 477
(1810.21 MJ·t-1 of macauba fruit × 900 t·ha-1) / 30 yr = 54.3 GJ·ha-1·yr-1, the energy input would 478
be higher for macauba, but its higher biodiesel yield (ca. 200 l biodiesel·t-1 fruit for macauba) 479
would compensate for it, in such a way that the total energy input in GJ·t-1·yr-1 biodiesel would 480
be very similar: 10.66 for African oil palm vs. 10.86 GJ·t-1·yr-1 biodiesel for macauba palm.
481
Apropos of other energy crops, Siregar et al. (2015) studied the LCA of African oil palm and 482
physic nut (Jatropha curcas L.) as a feedstock for biodiesel production in Indonesia. They 483
found that the values of 100-year GWP (IPCC 2007) for producing 1 t of biodiesel fuel from 484
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African oil palm and Jatropha curcas were 2568.82 and 1733.67 kg CO2eq, respectively. Upon 485
subtraction of the oil extraction and biodiesel production stages, the impact derived from the 486
planting, cultivation and harvesting stages would add up to 1378.36 and 817.25 kg CO2eq·t-1 487
biodiesel, respectively. Assuming that the biodiesel yield per ton of macauba fruit is ca. 200 l 488
(0.184 t), and considering that for 1 ton of fruit the GWP was 141.54 kg CO2eq (recalculated with 489
IPCC 2007 methodology), the GWP100 per ton of macauba-derived biodiesel would be around 490
769.2 kg CO2eq, so it would be lower than those of the other two crops. Regarding the energy 491
consumption, it was 25667 MJ·t-1 biodiesel for African oil palm and 15872 MJ·t-1 biodiesel for 492
Jatropha curcas, higher than the 9838.1 MJ·t-1 biodiesel for macauba.
493
In the case of biodiesel derived from castor-bean (Ricinus communis) oil, Amouri et al.
494
(2016) reported that GHG emissions during the cultivation stage were 452.38 kg CO2eq·t-1. 495
Assuming that the oil content in castor-seeds is ca. 43%, and taking into consideration its density 496
(0.96 g·cm-3), 412.8 l oil per ton of seeds would be obtained, resulting in a GWP of 1.09 kg CO2eq·l- 497
1 biodiesel for Ricinus communis. In turn, the GWP emissions for macauba (using Impact 2002+
498
methodology, to allow a certain degree of comparison) would be noticeably lower (147.38 kg 499
CO2eq/200 l biodiesel, i.e., ca. 0.74 kg CO2eq·l-1 biodiesel).
500
Finally, Schmidt (2015) compared the IPCC's GWP100 for several different refined vegetable 501
oils and found that the agricultural stage involved 3016, 976, 718 and 949 kg CO2eq·t-1 of oil for 502
palm oil, rapeseed oil, sunflower oil and peanut oil, respectively. Considering that the estimated 503
GWP100 for macauba (recalculated with IPCC 2007 methodology) was 141.54 kg CO2eq·t-1 of fruit 504
and that 25 t fruit·ha-1·yr-1 result in 6200 kg of oil·ha-1·yr-1 (0.248 conversion factor), the GWP100 505
value per ton of oil would be 570.7 kg CO2eq, lower than those of the four aforementioned oils.
506 507
4.2. Adaptation and mitigation strategies 508
As noted by Dislich et al. (2017), strategies are required to improve the capacity for local 509
adaptation to reduce climate impacts and maintain regional stability in oil production. An in- 510
depth analysis of the opportunities offered by macauba palm cultivation to mitigate the share of 511
GWP emissions that directly depend on land use and land management techniques is beyond the 512
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scope of this study (for an analysis of bioenergy as a climate mitigation option within a 2 ºC 513
target, the interested reader is referred, for instance, to the recent works by Creutzig et al.
514
(2015); Röder and Thornley (2016); Souza et al. (2017b)). Nonetheless, in view of the LCA 515
results, which show that the impact in all three indicators could mostly be ascribed to NPK 516
fertilization, a brief comment on this matter may be useful.
517
Adaptive nitrogen and soil health management strategies should be regarded as a must with a 518
view to mitigating and adapting to climate change in the case of macauba cultivation. An overall 519
reduction of N-fertilizer use would lead to a significant reduction of the associated CO2
520
emissions from the Haber-Bosch process that produces these fertilizers, from their 521
transportation and application, and would reduce losses of nitrous oxide too, which is by far the 522
largest source of greenhouse gas emissions associated with agriculture. To reduce N2O 523
emissions from applied N fertilizer, the four main management factors (commonly known as the 524
4R’s) should be implemented: namely, right N application rate; right formulation (fertilizer 525
type; possible replacement by other fertilizers that are equally effective but of less polluting 526
origin or waste that can enter the life cycle of the product mainly by fertilizers of organic 527
origin); right timing of application; and right placement. Best agricultural practices should be 528
established with the help of sensors and an adequate fertilizer plan adapted to the needs of the 529
crop and the expected productions. A reduction of nutrient losses by up to an average of 30 530
percent may be obtained with such improved management practices, according to the 531
International Fertilizer Association.
532
The use of technologies such as foliar application; coated soluble granules (to allow 533
controlled release of nutrients in the root zone); urea deep placement (to improve nitrogen 534
recovery); addition of inhibitors (to slow the conversion of urea fertilizer to ammonia and 535
thereby minimize potential ammonia loss to the atmosphere); and fertigation are also amongst 536
the options that would need to be contemplated so as to effectively minimize the negative 537
impacts of fertilizers on the environment. Besides, organic agriculture strategies should be 538
examined, in line with IPCC’s Assessment Report, as they offer added benefits (e.g., recycling 539
of crop waste intensifies biological activities of soils, enhances biodiversity as well as nitrogen 540
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fixation and improving phosphorous availability by symbiosis; organic farming builds up soil 541
fertility and increases or conserves soil organic matter; it can synchronize supply and demand of 542
nutrients, conserving water and sequestering CO2 into the soil, etc.). In short, improving soil 543
health, carbon and nitrogen management would provide win-win opportunities, increase profits 544
and decrease environmental losses, as shown, for instance, in the study by Rodrigues et al.
545
(2014) mentioned above.
546
Finally, attention should be paid to the fact that improvements will be required in the 547
macauba palm nutrients uptake efficiency by breeding for suitable root systems: prolonged root 548
uptake and better remobilization of nutrients are targets for breeding, provided there is sufficient 549
plasticity of these characteristics (Rival, 2017).
550 551
5. CONCLUSIONS 552
A full environmental evaluation, including not only global warming potential and energy 553
consumption, but also other categories related to impacts to soil, water, air, human health, and 554
ecosystems was conducted for Acrocomia aculeate planting, cultivation and harvesting, using 555
IPCC 2013, CED and EI-99 methodologies. It was found that the introduction of macauba palm 556
as a candidate for the production of biofuels a priori presents environmental benefits as 557
compared to energy crops such as rapeseed, sunflower, castor seed or physic nut. Moreover, the 558
100-year GWP (ca. 140 kg CO2eq·t-1 of fruit) and CED (1810.21 MJ·t-1 of fruit) associated with 559
its cultivation would be comparable to those of Elaeis guineensis. Nonetheless, from the LCA it 560
becomes apparent that there is room for improvement in terms of the impacts produced, in 561
particular in relation to fertilizers, which contributed with ca. 90% of the GHG emissions, 562
energy consumed by the crop and damage to all the environmental impact categories.
563
Consequently, future lines of research aimed at the development of alternative fertilizer 564
management schemes, including for instance the replacement of conventional NPK solid 565
fertilizers by foliar fertilizers or compost, should have a remarkable effect on the sustainability 566
of this emerging energy crop.
567 568
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ACKNOWLEDGMENTS 569
P.M.-R. would like to thank Santander Universidades for its financial support through the 570
“Becas Iberoamérica Jóvenes Profesores e Investigadores, España” scholarship program.
571 572
CONFLICTS OF INTEREST 573
The authors declare no conflict of interest.
574 575
REFERENCES 576
Ali, B.M., Berentsen, P.B.M., Bastiaansen, J.W.M., Oude Lansink, A., 2017a. A stochastic bio- 577
economic pig farm model to assess the impact of innovations on farm performance. Animal 578
12, 1-12.
579
Ali, B.M., van Zanten, H.H.E., Berentsen, P., Bastiaansen, J.W.M., Bikker, P., Lansink, A.O., 580
2017b. Environmental and economic impacts of using co-products in the diets of finishing 581
pigs in Brazil. Journal of Cleaner Production 162, 247-259.
582
Altino, H.O.N., Costa, B.E.S., Cunha, R.N.d., 2017. Biosorption optimization of Ni(II) ions on 583
macauba (Acrocomia aculeata) oil extraction residue using fixed-bed column. J. Environ.
584
Chem. Eng. 5, 4895-4905.
585
Amouri, M., Mohellebi, F., Zaïd, T.A., Aziza, M., 2016. Sustainability assessment of Ricinus 586
communis biodiesel using LCA approach. Clean Technologies and Environmental Policy 19, 587
749-760.
588
Araújo, K., Mahajan, D., Kerr, R., Silva, M.d., 2017. Global biofuels at the crossroads: An 589
overview of technical, policy, and investment complexities in the sustainability of biofuel 590
development. Agriculture 7, 32.
591
Berton, L.H.C., de Azevedo Filho, J.A., Siqueira, W.J., Colombo, C.A., 2013. Seed germination 592
and estimates of genetic parameters of promising macaw palm (Acrocomia aculeata) 593
progenies for biofuel production. Ind. Crop. Prod. 51, 258-266.
594
Preprint
Bhering, L.L., 2009. Macaúba: matéria-prima nativa com potencial para a produção de biodiesel, 595
Embrapa Agroenergía (CNPAE). Empresa Brasileira de Pesquisa Agropecuária (Ministério da 596
Agricultura, Pecuária e Abastecimento), Brazil, pp. 1-4.
597
Cardoso, A., Laviola, B.G., Santos, G.S., de Sousa, H.U., de Oliveira, H.B., Veras, L.C., 598
Ciannella, R., Favaro, S.P., 2017. Opportunities and challenges for sustainable production of 599
A. aculeata through agroforestry systems. Ind. Crop. Prod. 107, 573-580.
600
Cargnin, A.C., Junqueira, N.T.V., Fogaça, C.M., 2008. Potencial da macaubeira como fonte de 601
matéria-prima para produção de biodiesel, Documentos, Embrapa Cerrados. Empresa 602
Brasileira de Pesquisa Agropecuária (Ministério da Agricultura, Pecuária e Abastecimento), 603
Planaltina, Brazil, pp. 1-54.
604
Castanheira, É.G., Freire, F., 2016. Environmental life cycle assessment of biodiesel produced 605
with palm oil from Colombia. The International Journal of Life Cycle Assessment 22, 587- 606
600.
607
Castro, C.A.d.O., Resende, R.T., Kuki, K.N., Carneiro, V.Q., Marcatti, G.E., Cruz, C.D., 608
Motoike, S.Y., 2017. High-performance prediction of macauba fruit biomass for agricultural 609
and industrial purposes using Artificial Neural Networks. Ind. Crop. Prod. 108, 806-813.
610
César, A.d.S., Almeida, F.d.A., de Souza, R.P., Silva, G.C., Atabani, A.E., 2015. The prospects 611
of using Acrocomia aculeata (macaúba) a non-edible biodiesel feedstock in Brazil. Renewable 612
and Sustainable Energy Reviews 49, 1213-1220.
613
Cherubini, F., Strømman, A.H., 2011. Life cycle assessment of bioenergy systems: State of the 614
art and future challenges. Bioresour. Technol. 102, 437-451.
615
Chiaramonti, D., Recchia, L., 2010. Is life cycle assessment (LCA) a suitable method for 616
quantitative CO2 saving estimations? The impact of field input on the LCA results for a pure 617
vegetable oil chain. Biomass Bioenergy 34, 787-797.
618
Ciconini, G., Favaro, S.P., Roscoe, R., Miranda, C.H.B., Tapeti, C.F., Miyahira, M.A.M., Bearari, 619
L., Galvani, F., Borsato, A.V., Colnago, L.A., Naka, M.H., 2013. Biometry and oil contents 620
of Acrocomia aculeata fruits from the Cerrados and Pantanal biomes in Mato Grosso do Sul, 621
Brazil. Ind. Crop. Prod. 45, 208-214.
622
Preprint
Coimbra, M.C., Jorge, N., 2012. Fatty acids and bioactive compounds of the pulps and kernels of 623
Brazilian palm species, guariroba (Syagrus oleraces), jerivá (Syagrus romanzoffiana) and 624
macaúba (Acrocomia aculeata). J. Sci. Food Agric. 92, 679-684.
625
Colombo, C.A., Chorfi Berton, L.H., Diaz, B.G., Ferrari, R.A., 2017. Macauba: a promising 626
tropical palm for the production of vegetable oil. Oilseeds and fats, Crops and Lipids, 1-9.
627
Costa Júnior, M.B.d., Arouca, C.L.C., Maciel, M.P., Aiura, F.S., Fontes, D.d.O., Rosa, B.O., 628
Lima, C.d.A., Fernandes, I.S., 2015. Torta da polpa da macaúba para suínos em terminação.
629
Revista Brasileira de Saúde e Produção Animal 16, 325-336.
630
Creutzig, F., Ravindranath, N.H., Berndes, G., Bolwig, S., Bright, R., Cherubini, F., Chum, H., 631
Corbera, E., Delucchi, M., Faaij, A., Fargione, J., Haberl, H., Heath, G., Lucon, O., Plevin, R., 632
Popp, A., Robledo-Abad, C., Rose, S., Smith, P., Stromman, A., Suh, S., Masera, O., 2015.
633
Bioenergy and climate change mitigation: an assessment. GCB Bioenergy 7, 916-944.
634
Dario, M.F., Oliveira, F.F., Marins, D.S.S., Baby, A.R., Velasco, M.V.R., Löbenberg, R., Bou- 635
Chacra, N.A., 2018. Synergistic photoprotective activity of nanocarrier containing oil of 636
Acrocomia aculeata (Jacq.) Lodd. Ex. Martius—Arecaceae. Ind. Crop. Prod. 112, 305-312.
637
del Río, J.C., Evaristo, A.B., Marques, G., Martín-Ramos, P., Martín-Gil, J., Gutiérrez, A., 2016.
638
Chemical composition and thermal behavior of the pulp and kernel oils from macauba palm 639
(Acrocomia aculeata) fruit. Ind. Crop. Prod. 84, 294-304.
640
Delucchi, M.A., 2010. Impacts of biofuels on climate change, water use, and land use. Ann. N.Y.
641
Acad. Sci. 1195, 28-45.
642
Dislich, C., Keyel, A.C., Salecker, J., Kisel, Y., Meyer, K.M., Auliya, M., Barnes, A.D., Corre, 643
M.D., Darras, K., Faust, H., Hess, B., Klasen, S., Knohl, A., Kreft, H., Meijide, A., 644
Nurdiansyah, F., Otten, F., Pe'er, G., Steinebach, S., Tarigan, S., Tölle, M.H., Tscharntke, T., 645
Wiegand, K., 2017. A review of the ecosystem functions in oil palm plantations, using forests 646
as a reference system. Biological Reviews 92, 1539-1569.
647
European Commission, Joint Research Centre, Institute for Environment and Sustainability, 648
2010. International Reference Life Cycle Data System (ILCD) Handbook - General guide for 649
Preprint
Life Cycle Assessment, Detailed guidance. EUR 24708 EN. Publications Office of the 650
European Union, Luxembourg.
651
Evaristo, A.B., Grossi, J.A.S., Carneiro, A.d.C.O., Pimentel, L.D., Motoike, S.Y., Kuki, K.N., 652
2016a. Actual and putative potentials of macauba palm as feedstock for solid biofuel 653
production from residues. Biomass Bioenergy 85, 18-24.
654
Evaristo, A.B., Grossi, J.A.S., Pimentel, L.D., de Melo Goulart, S., Martins, A.D., dos Santos, 655
V.L., Motoike, S., 2016b. Harvest and post-harvest conditions influencing macauba 656
(Acrocomia aculeata) oil quality attributes. Ind. Crop. Prod. 85, 63-73.
657
Falasca, S., Ulberich, A., Pitta-Alvarez, S., 2016. Development of agroclimatic zoning model to 658
delimit the potential growing areas for macaw palm (Acrocomia aculeata). Theoretical and 659
Applied Climatology 129, 1321-1333.
660
Frischknecht, R., Jungbluth, N., Althaus, H.-J., Bauer, C., Doka, G., Dones, R., Hischier, R., 661
Hellweg, S., Humbert, S., Köllner, T., 2007. Implementation of life cycle impact assessment 662
methods: Data v.2.0 (Ecoinvent report no. 3), Dübendorf, Switzerland, p. 151.
663
Galembeck, F., Abreu Filho, P., 2017. Perspectives for biomass production and use in Brazil.
664
Revista Virtual de Química 9, 274-293.
665
Harsono, S.S., Prochnow, A., Grundmann, P., Hansen, A., Hallmann, C., 2012. Energy balances 666
and greenhouse gas emissions of palm oil biodiesel in Indonesia. GCB Bioenergy 4, 213-228.
667
Henrique Bernardes Pereira, J., Lúcio Salomon Cabral Filho, S., Gabriele de Queroz Roriz, C., 668
Boechat Bernardes, C., Morais Barbosa, T., Ribeiro Roos, L., Santana, Â., Batista Lopes, J., 669
Sayori Murata, L., 2013. Nutritional value of macauba pulp presscake (Acrocomia aculeata) 670
for growing pigs [tr.]. Universidade de Brasilia, Brasilia, Brazil.
671
IPCC, 2014. Climate Change 2013: The Physical Science Basis. Contribution of Working Group 672
I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.
673
Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
674
Iriarte, A., Rieradevall, J., Gabarrell, X., 2012. Transition towards a more environmentally 675
sustainable biodiesel in South America: The case of Chile. Applied Energy 91, 263-273.
676
Preprint
Lescano, C.H., Oliveira, I.P., Silva, L.R., Baldivia, D.S., Sanjinez-Argandoña, E.J., Arruda, E.J., 677
Moraes, I.C.F., Lima, F.F., 2015. Nutrients content, characterization and oil extraction from 678
Acrocomia aculeata (Jacq.) Lodd. fruits. African Journal of Food Science 9, 113-119.
679
Lescano, C.H., Sanjinez-Argandoña, E.J., de Arruda, E.J., Kassuya, C.A.L., Moraes, I.C.F., 2014.
680
Acrocomia aculeata (Jacq.) Lodd. oil microencapsulation by complex coacervation:
681
Preservation of bioactive compounds. Journal of Encapsulation and Adsorption Sciences 04, 682
105-113.
683
Lopes, D.C., Steidle Neto, A.J., 2011. Potential crops for biodiesel production in Brazil: a review.
684
World Journal of Agricultural Sciences 7, 206-217.
685
Lopes, D.d.C., Steidle Neto, A.J., Mendes, A.A., Pereira, D.T.V., 2013. Economic feasibility of 686
biodiesel production from Macauba in Brazil. Energy Economics 40, 819-824.
687
Luis, Z.G., Scherwinski-Pereira, J.E., 2017. A simple and efficient protocol for the 688
cryopreservation of zygotic embryos of macaw palm [Acrocomia Aculeata (Jacq.) Lodd. Ex 689
Mart.], a tropical species with a capacity for biofuel production. Cryoletters 38, 7-16.
690
Machado, W., Guimarães, M.F., Lira, F.F., Santos, J.V.F., Takahashi, L.S.A., Leal, A.C., Coelho, 691
G.T.C.P., 2015. Evaluation of two fruit ecotypes (totai and sclerocarpa) of macaúba 692
(Acrocomia aculeata). Ind. Crop. Prod. 63, 287-293.
693
McManus, M.C., Taylor, C.M., 2015. The changing nature of life cycle assessment. Biomass 694
Bioenergy 82, 13-26.
695
Ministério do Desenvolvimento Agrário, 2014. Macaúba - Diretrizes e recomendações técnicas 696
para adoção de boas práticas de manejo para o extrativismo do fruto da macaúba/bocaiúva 697
Brazilia, Brazil, p. 52.
698
Montoya, S.G., Motoike, S.Y., Kuki, K.N., Couto, A.D., 2016. Fruit development, growth, and 699
stored reserves in macauba palm (Acrocomia aculeata), an alternative bioenergy crop. Planta 700
244, 927-938.
701
Motoike, S., Kuki, K., 2009. The potential of macaw palm (Acrocomia aculeata) as source of 702
biodiesel in Brazil. International Review of Chemical Engineering 1, 632-635.
703
Preprint
Muench, S., Guenther, E., 2013. A systematic review of bioenergy life cycle assessments. Applied 704
Energy 112, 257-273.
705
Ndong, R., Montrejaud-Vignoles, M., Saint Girons, O., Gabrielle, B., Pirot, R., Domergue, M., 706
Sablayrolles, C., 2009. Life cycle assessment of biofuels from Jatropha curcas in West Africa:
707
a field study. GCB Bioenergy 1, 197-210.
708
Oliveira, A.I.T.d., Mahmoud, T.S., Nascimento, G.N.L.d., Silva, J.F.M.d., Pimenta, R.S., Morais, 709
P.B.d., 2016. Chemical composition and antimicrobial potential of palm leaf extracts from 710
babaçu (Attalea speciosa), buriti (Mauritia flexuosa), and macaúba (Acrocomia aculeata). The 711
Scientific World Journal 2016, 1-5.
712
Ossés de Eicker, M., Hischier, R., Kulay, L.A., Lehmann, M., Zah, R., Hurni, H., 2010. The 713
applicability of non-local LCI data for LCA. Environ. Impact Assess. Rev. 30, 192-199.
714
Pereira, M.R.d.N., Valério, P.P., Grande, S.C., Andrade, M.H.C.d., 2016. Microwave irradiation 715
as an alternative process for biodiesel production using macauba oil (Acrocomia aculeata).
716
Journal of Chemical Engineering and Chemistry 2, 034-046.
717
Pires, T.P., dos Santos Souza, E., Kuki, K.N., Motoike, S.Y., 2013. Ecophysiological traits of the 718
macaw palm: A contribution towards the domestication of a novel oil crop. Ind. Crop. Prod.
719
44, 200-210.
720
Plevin, R.J., Delucchi, M.A., Creutzig, F., 2014. Using attributional life cycle assessment to 721
estimate climate-change mitigation benefits misleads policy makers. Journal of Industrial 722
Ecology 18, 73-83.
723
Rajagopal, D., 2014. Consequential life cycle assessment of policy vulnerability to price effects.
724
Journal of Industrial Ecology 18, 164-175.
725
Recchia, L., 2011. Multicriteria analysis and LCA techniques: with applications to agro- 726
engineering problems. Springer-Verlag, London ; New York.
727
Rival, A., 2017. Breeding the oil palm (Elaeis guineensis Jacq.) for climate change. Ocl 24.
728
Rivera-Méndez, Y.D., Rodríguez, D.T., Romero, H.M., 2017. Carbon footprint of the production 729
of oil palm (Elaeis guineensis) fresh fruit bunches in Colombia. Journal of Cleaner Production 730
149, 743-750.
731